Exoskeletons are wearable mechanical devices that may possess a kinematic configuration similar to that of the human body and that may have the ability to follow the movements of the user's extremities. Powered exoskeletons may be designed to produce contact forces to assist the user in performing a motor task. In recent years, a large number of lower-limb exoskeleton systems and their associated control methods have been developed, both as research tools for the study of human gait (Ferris, D., Sawicki, G., Daley, M. “A physiologist's perspective on robotic exoskeletons for human locomotion.” International Journal of Humanoid Robotics (2007) 4: pp 507-52) and as rehabilitation tools for patients with stroke and/or other locomotor disorders (Dollar, A., Herr, H. “Lower extremity exoskeletons and active orthoses: Challenges and state of the art.” IEEE Transactions on Robotics (2008) 24(1): pp 144-158). In a parallel development, a number of lightweight, autonomous exoskeletons have been designed with the aim of assisting impaired and/or aged users in daily-living situations (Ekso Bionics™ “Ekso bionics—an exoskeleton bionic suit or a wearable robot that helps people walk again.” (2013) URL www.eksobionics.com).
A wide variety of assistive strategies and control methods for exoskeleton devices have been developed and tested with varying levels of success. For example, an assistive strategy may be based on how exoskeleton forces or torques are applied to the human body. This strategy may treat the human body as a multi-body system composed of rigid, actuated links, such as (a) Propulsion of the body's center of mass, especially during the stance phase of walking (Kazerooni, H., Racine, J., Huang, R. Land Steger “On the control of the berkeley lower extremity exoskeleton (BLEEX).” In: Proceedings of the IEEE International Conference on Robotics and Automation ICRA (2005), pp 4353-4360); (b) Propulsion of the unconstrained leg, for example during the swing phase of walking (Veneman, J., Ekkelenkamp, R., Kruidhof, R., Van der Helm, F., Van der Kooij, H. “Design of a series elastic- and Bowden cable-based actuation system for use as torque-actuator in exoskeleton-type training.” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2005) pp 496-499); or (c) Gravitational support of the extremities (Banala, S., Kim, S., Agrawal, S., Scholz, J. “Robot assisted gait training with active leg exoskeleton (ALEX).” Neural Systems and Rehabilitation Engineering, IEEE Transactions (2009) on 17(1) pp 2-8).
Another assistive strategy may be based on the intended effect on the dynamics or physiology of human movement. For example, (a) Reducing the muscle activation required for walking at a given speed (Kawamoto, H., Lee, S., Kanbe, S., Sankai, Y. “Power assist method for HAL-3 using EMG-based feedback controller.” In: Systems, Man and Cybernetics, IEEE International Conference (2003) in, vol 2, pp 1648-1653; Gordon, K, Kinnaird, C, Ferris, D. “Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.” Journal of Neurophysiology (2013) 109(7): pp 1804-1814); (b) Increasing the comfortable walking speed for a given level of muscle effort (Norris, J., Granata, K. P., Mitros, M. R., Byrne, E. M., Marsh, A. P. “Effect of augmented plantarflexion power on preferred walking speed and economy in young and older adults.” (2007) Gait & Posture 25: pp 620-627). The aforementioned may be attained either through an increase in mean stride length (Sawicki, G., Ferris, D. “Powered ankle exoskeletons reveal the metabolic cost of plantar flexor mechanical work during walking with longer steps at constant step frequency.” Journal of Experimental Biology (2009) 212: pp 21-31) or through mean stepping frequency (Lee, S., Sankai, Y. “The natural frequency-based power assist control for lower body with HAL-3.” IEEE International Conference on Systems, Man and Cybernetics (2003) 2: pp 1642-1647); (c) Reducing the metabolic cost of walking (Sawicki, G., Ferris, D. “Mechanics and energetics of level walking with powered ankle exoskeletons.” Journal of Experimental Biology (2008) 211: pp 1402-1413; Mooney, L., Rouse, E., Herr. H. “Autonomous exoskeleton reduces metabolic cost of human walking during load carriage.” Journal of NeuroEngineering and Rehabilitation (2014) 11(1): pp 80); (d) Correcting anomalies of the gait trajectory (Banala, S., Kim, S., Agrawal, S., Scholz, J. “Robot assisted gait training with active leg exoskeleton (ALEX)”. Neural Systems and Rehabilitation Engineering, IEEE Transactions (2009) on 17(1): pp 2-8; Van Asseldonk, E., Ekkelenkamp, R., Veneman, J., Van der Helm, F., Van der Kooij, H. “Selective control of a subtask of walking in a robotic gait trainer (LOPES).” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2007) pp 841-848); or (e) Balance recovery and dynamic stability during walking European Commission (CORDIS). “Balance Augmentation in Locomotion, through Anticipative, Natural and Cooperative control of Exoskeletons (BALANCE).” (2013) URL cordis.europa.eu/projects/ren/106854_en.html).
Assistive strategies based on the intended effect on the dynamics or physiology of human movement, may occur on different time scales. The effects sought may range from immediate, as in the case of balance recovery and dynamic stability, to long-term, as in the case of gait anomaly correction, which normally may become apparent over the course of several training sessions.
The approaches listed above may require the estimation of one or more of the following types of variables: kinematic state of the limb and its time derivatives, muscle torques and intended motion trajectory. Accurate estimation may be a challenging task, especially in the case of the latter two.
Despite the different assistive strategies cited above, as well as their differences in time scale, the basic interaction that may occur when wearing an exoskeleton is generally the same: the exoskeleton attempts to exert controlled forces or torques on the body segments of the user. One may define the assistive torque as the torque that should be exerted at the exoskeleton's points of contact with the user in order to help the user complete a desired motion. Designing a system and method to track a desired assistive torque may be difficult. Even assuming that reasonable estimates of the system's parameters and states may be obtained, in general, it may not be possible for an exoskeleton to deliver a completely arbitrary assistive torque profile. To do so may require the exoskeleton to behave as a pure torque source. In other words, the exoskeleton may have to display zero mechanical impedance at its port(s) of interaction with the user. Mechanical impedance may be a measure of how much the exoskeleton resists motion when subjected to a harmonic force. The mechanical impedance of a point on the exoskeleton may be defined as a ratio of the force applied at a point to the resulting velocity at that point. However, in practice, most exoskeleton mechanisms display finite mechanical impedance, thereby acting as a load on the user's limbs. In the absence of control, the coupled system formed by the leg and the exoskeleton may be less mobile than the unassisted leg. For this reason, many assistive devices feature a layer of feedback control that may be designed to reduce the exoskeleton's impedance, especially the friction effects on the user (Veneman, J., Ekkelenkamp, R., Kruidhof, R., Van der Helm, F., Van der Kooij, H. “Design of a series elastic- and Bowden cable-based actuation system for use as torque-actuator in exoskeleton-type training.” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2005) pp 496-499). However, the feedback control may be used not only to reduce the exoskeleton's impedance but, with proper hardware and control design, to turn the exoskeleton's port impedance into a source of assistance to the user. It would thus be desirable to provide a system and method to produce this form of impedance-based assistance. The system and method may assist by producing a desired dynamic response of the human leg, wherein the exoskeleton control may allow the leg of the user to obey an admittance model defined by target values of natural frequency, resonant peak magnitude and zero-frequency response.